Difference between revisions of "Publications/darbon.05.ibpria"
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| abstract = This paper deals with the minimization of the total variation under a convex data fidelity term. We propose an algorithm which computes an exact minimizer of this problem. The method relies on the decomposition of an image into its level sets. Using these level sets, we map the problem into optimizations of independent binary Markov Random Fields. Binary solutions are found thanks to graph-cut techniques and we show how to derive a fast algorithm. We also study the special case when the fidelity term is the $L^1$-norm. Finally we provide some experiments. |
| abstract = This paper deals with the minimization of the total variation under a convex data fidelity term. We propose an algorithm which computes an exact minimizer of this problem. The method relies on the decomposition of an image into its level sets. Using these level sets, we map the problem into optimizations of independent binary Markov Random Fields. Binary solutions are found thanks to graph-cut techniques and we show how to derive a fast algorithm. We also study the special case when the fidelity term is the $L^1$-norm. Finally we provide some experiments. |
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| lrdekeywords = Image |
| lrdekeywords = Image |
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address = <nowiki>{</nowiki>Estoril, Portugal<nowiki>}</nowiki>, |
address = <nowiki>{</nowiki>Estoril, Portugal<nowiki>}</nowiki>, |
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month = jun, |
month = jun, |
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| − | project = <nowiki>{</nowiki>Image<nowiki>}</nowiki>, |
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abstract = <nowiki>{</nowiki>This paper deals with the minimization of the total |
abstract = <nowiki>{</nowiki>This paper deals with the minimization of the total |
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variation under a convex data fidelity term. We propose an |
variation under a convex data fidelity term. We propose an |
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Revision as of 12:13, 26 April 2016
- Authors
- Jérôme Darbon, Marc Sigelle
- Where
- Proceedings of the 2nd Iberian Conference on Pattern Recognition and Image Analysis (IbPRIA)
- Place
- Estoril, Portugal
- Type
- inproceedings
- Publisher
- Springer-Verlag
- Projects
- Image"Image" is not in the list (Vaucanson, Spot, URBI, Olena, APMC, Tiger, Climb, Speaker ID, Transformers, Bison, ...) of allowed values for the "Related project" property.
- Keywords
- Image
- Date
- 2005-01-18
Abstract
This paper deals with the minimization of the total variation under a convex data fidelity term. We propose an algorithm which computes an exact minimizer of this problem. The method relies on the decomposition of an image into its level sets. Using these level sets, we map the problem into optimizations of independent binary Markov Random Fields. Binary solutions are found thanks to graph-cut techniques and we show how to derive a fast algorithm. We also study the special case when the fidelity term is the $L^1$-norm. Finally we provide some experiments.
Bibtex (lrde.bib)
@InProceedings{ darbon.05.ibpria,
author = {J\'er\^ome Darbon and Marc Sigelle},
title = {A Fast and Exact Algorithm for Total Variation
Minimization},
booktitle = {Proceedings of the 2nd Iberian Conference on Pattern
Recognition and Image Analysis (IbPRIA)},
publisher = {Springer-Verlag},
volume = 3522,
pages = {351--359},
year = 2005,
address = {Estoril, Portugal},
month = jun,
abstract = {This paper deals with the minimization of the total
variation under a convex data fidelity term. We propose an
algorithm which computes an exact minimizer of this
problem. The method relies on the decomposition of an image
into its level sets. Using these level sets, we map the
problem into optimizations of independent binary Markov
Random Fields. Binary solutions are found thanks to
graph-cut techniques and we show how to derive a fast
algorithm. We also study the special case when the fidelity
term is the $L^1$-norm. Finally we provide some
experiments.}
}